An accurate and Multi-faceted Reputation scheme for cloud computing

Miao Wang, Gui Ling Wang, Jie Tian, Hanwen Zhang, Yu Jun Zhang

Research output: Contribution to journalConference articlepeer-review

7 Scopus citations

Abstract

With the rapid growth of cloud computing, the importance of a reputation system for cloud computing services has attracted a lot of attention. Building an objective and reliable reputation scheme has been crucial to promote the development of cloud computing. To address the challenges of reputation evaluation in cloud computing, including the diverse nature of cloud services and intricacy of malicious ratings, an Accurate and Multi-faceted Reputation scheme for cloud computing (AMRep) is proposed. As the reputation systems of cloud computing are exposed to new vulnerabilities, AMRep introduces a couple of malicious rating detection approaches to improve the accuracy of reputation calculation. Additionally, we establish a multi-faceted reputation evaluation method, which can help user assess and choose cloud services from different angles. Experiments reveal that our AMRep scheme can effectively defend against malicious ratings, and accurately calculate the reputation values of cloud services.

Original languageEnglish (US)
Pages (from-to)466-473
Number of pages8
JournalProcedia Computer Science
Volume34
DOIs
StatePublished - 2014
Event9th International Conference on Future Networks and Communications, FNC 2014 and the 11th International Conference on Mobile Systems and Pervasive Computing, MobiSPC 2014 - Niagara Falls, ON, Canada
Duration: Aug 17 2014Aug 20 2014

All Science Journal Classification (ASJC) codes

  • Computer Science(all)

Keywords

  • Cloud computing
  • Diverse nature
  • Malicious rating
  • Reputation evaluation

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